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services/asf-worker/app/config.py

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+"""Settings."""
+
+from __future__ import annotations
+
+from functools import lru_cache
+
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+
+class WorkerSettings(BaseSettings):
+    model_config = SettingsConfigDict(
+        env_file=".env", case_sensitive=False, extra="ignore"
+    )
+    asf_env: str = "development"
+    asf_log_level: str = "INFO"
+    rabbitmq_uri: str = "amqp://azurian:StrongPassword123!@172.19.40.201:5672/asf"
+    mongo_uri: str = "mongodb://172.19.40.102:27017,172.19.40.103:27017/asf?replicaSet=rs0"
+    mongo_db: str = "asf"
+    ai_gateway_provider: str = "mock"
+
+    # Queue → routing key bindings consumed by this worker.
+    # A single worker can subscribe to a subset; in production you'd run
+    # separate worker deployments per queue pool.
+    queues: list[str] = [
+        "asf.ai.interactive",
+        "asf.ai.background",
+        "asf.indexing",
+        "asf.code_analysis",
+        "asf.testing",
+        "asf.devops",
+        "asf.notifications",
+    ]
+
+    # If true, AI jobs invoke the AI Gateway and write results back.
+    enable_ai_handlers: bool = True
+
+    worker_id: str = "asf-worker-1"
+    prefetch_count: int = 4
+
+
+@lru_cache(maxsize=1)
+def get_settings() -> WorkerSettings:
+    return WorkerSettings()